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Research On Evaluation Of Competitiveness Of Petroleum Engineering Service Enterprises Based On

Posted on:2015-06-26Degree:MasterType:Thesis
Country:ChinaCandidate:Y J JiangFull Text:PDF
GTID:2279330434954838Subject:Petroleum engineering management
Abstract/Summary:PDF Full Text Request
With the acceleration development of reform and opening up, the market economic system established steadily, China’s petroleum engineering technical services in the domestic market gradually formed and perfected. At the same time, in the backdrop of the strategy of "going out" implementation, CNPC, SINOPEC and CNOOC three state-owned oil company, oil engineering and technical services to realize the transnational operation. Then, in the process of oil clothing market fully open, exacerbate global petroleum engineering technical service market competition strength. Petroleum engineering technology service enterprises want to or eliminated by the market, and to obtain sustainable development, we must strengthen the competitiveness of enterprises.In this paper, from the related theory of enterprise competitiveness, scholars at home and abroad for reference, the related research results about enterprise competitiveness, and combining with the characteristics of petroleum engineering technology service industry, we analyzed the components of petroleum engineering technology service enterprise competitiveness. With the help of three elements RCI (resource, ability, innovation), the evaluation index system of petroleum engineering service enterprise competitiveness based on RCI is established. By using the rough set-neural network model, we made the quantitative evaluation of petroleum engineering service enterprise competitiveness. In this article, you can see that the rough set-neural network model application petroleum engineering technology service enterprise competitiveness evaluation is feasible and has practical application value.
Keywords/Search Tags:Petroleum Engineering Technical Service, Enterprise Competitiveness, Resources-Ability-Innovation, Rough Set-neural Network, Evaluation Model
PDF Full Text Request
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